Kannan, R (Microsoft Research Labs., India)
Tuesday 25 March 2008, 16:15-16:45
Markov-chain Monte Carlo Methods

Kannan, R (Microsoft Research Labs., India) Tuesday 25 March 2008, 16:15-16:45 Markov-chain Monte Carlo Methods

A new probability inequality and some optimal concentration results

The past half-decade has seen an increasing interaction between combinatorialists, probabilists, computer scientists and theoretical physicists concerned broadly with the study of "probability theory on graphs" or "statistical mechanics on graphs".

The programme will build on this cross-fertilisation. It is particularly timely for a number of reasons:
* methods from mathematical physics are beginning to make their mark on previously intractable combinatorial problems;
* increasing computer power, together with the wide availability of symbolic-algebra packages, has brought the possibility of exploration of non-trivial examples; 
* phase transitions are increasingly being investigated on a wide variety of combinatorial structures, including matroids, set partitions and constraint satisfaction problems, as well as graphs.

Read more at: www.newton.ac.uk/programmes/CSM/

The past half-decade has seen an increasing interaction between combinatorialists, probabilists, computer scientists and theoretical physicists concerned broadly with the study of "probability theory on graphs" or "statistical mechanics on graphs". The programme will build on this cross-fertilisation. It is particularly timely for a number of reasons: * methods from mathematical physics are beginning to make their mark on previously intractable combinatorial problems; * increasing computer power, together with the wide availability of symbolic-algebra packages, has brought the possibility of exploration of non-trivial examples; * phase transitions are increasingly being investigated on a wide variety of combinatorial structures, including matroids, set partitions and constraint satisfaction problems, as well as graphs. Read more at: www.newton.ac.uk/programmes/CSM/

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A new probability inequality and some optimal concentration results

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